Systems and methods for estimating a three-dimensional pose

ABSTRACT

A method for estimating a pose of an oral hygiene device including a pattern and a plurality of groups of visual markers relative to a location includes (i) receiving image data reproducible as an image of at least a portion of the oral hygiene device; (ii) analyzing the image data to identify a region of interest within the image; (iii) identifying, using at least one of the one or more processors, all candidate visual markers within the region of interest; (iv) obtaining a first proposed three-dimensional pose of the oral hygiene device; (v) validating the first proposed three-dimensional pose of the oral hygiene device; and (vi) obtaining a second proposed three-dimensional pose of the oral hygiene device based on the validated first proposed three-dimensional pose.

FIELD OF THE PRESENT DISCLOSURE

The present disclosure relates generally to motion tracking, and moreparticularly, to systems and methods for estimating a pose of an oralhygiene device relative to a location.

BACKGROUND

Motion tracking systems are often used in a variety of applications,including, for example, in the medical field, in the movie and videogame industries, and the like. There remains a continued need for newsystems and methods are needed to accurately track the motion of anobject in all directions using a device, such as a smartphone, withlimited processing power. The present disclosure addresses these andother problems.

SUMMARY

According to some implementations of the present disclosure, a methodfor estimating a pose of an oral hygiene device including a pattern anda plurality of groups of visual markers relative to a location themethod includes receiving image data reproducible as an image of atleast a portion of the oral hygiene device. The method also includesanalyzing, using one or more processors, the image data to identify aregion of interest within the image, the region of interest including atleast a portion of the pattern therein, identifying, using at least oneof the one or more processors, all candidate visual markers within theregion of interest, and obtaining a first proposed three-dimensionalpose of the oral hygiene device. The method further includes validatingthe first proposed three-dimensional pose of the oral hygiene device,and obtaining a second proposed three-dimensional pose of the oralhygiene device based on the validated first proposed three-dimensionalpose.

According to other implementations of the present disclosure, a methodfor estimating a pose of an oral hygiene device including a pattern anda plurality of groups of visual markers relative to a location includes:(a) receiving image data reproducible as an image of at least a portionof the oral hygiene device; (b) analyzing, using one or more processors,the image data to identify a region of interest within the image, theregion of interest including at least a portion of the pattern therein;(c) responsive to identifying the region of interest, segmenting, usingat least one of the one or more processors, the region of interest intoa plurality of sub-regions, each of the plurality of sub-regions beingdefined by a plurality of pixels having a common color; (d) identifying,using at least one of the one or more processors, all candidate visualmarkers within the region of interest; (e) creating a plurality ofdistinct sets of the candidate visual markers; (f) selecting a first oneof the plurality of distinct sets of the candidate visual markers; (g)selecting a first one of a plurality of distinct sets of model markersassociated with a three-dimensional model of the oral hygiene device;(h) evaluating the selected set of the candidate visual markers and theselected set of model markers using a perspective-three-point algorithmto obtain a proposed three-dimensional pose of the oral hygiene device;(i) based on the proposed three-dimensional pose of the oral hygienedevice, predicting a position within the region of interest for apredetermined number of the candidate visual markers; (j) comparing thepredicted positions for the predetermined number of the candidate visualmarkers with actual positions of all of the candidate visual markerswithin the region of interest; (k) responsive to a determination that atleast a substantial portion of the predicted positions correspond withthe actual positions, validating the proposed three-dimensional pose;and (l) responsive to a determination that less than the substantialportion of the predicted positions correspond with the actual positions,repeating steps (f)-(k).

According to other implementations of the present disclosure, a motiontracking system includes an oral hygiene device, a tracking element, acamera, one or more processors, and a memory device. The oral hygienedevice includes a head and a handle. The tracking element is coupled tothe oral hygiene device and includes a pattern and a plurality of groupsof visual markers. The memory device stores instructions that, whenexecuted by at least one of the one or more processors cause the motiontracking system to: capture, using the camera, an image of at least aportion of the oral hygiene device; analyze, using at least one of theone or more processors, the image to identify a region of interestwithin the image, the region of interest including at least a portion ofthe pattern of the tracking element therein; identify, using at leastone of the one or more processors, all candidate visual markers withinthe region of interest; create a plurality of distinct sets of thecandidate visual markers; select a first one of the plurality ofdistinct sets of the candidate visual markers; select a first one of aplurality of distinct sets of model markers associated with athree-dimensional model of the oral hygiene device stored in the memorydevice; evaluate the selected set of the candidate visual markers andthe selected set of model markers using a perspective-three-pointalgorithm to obtain a proposed three-dimensional pose of the oralhygiene device; based on the proposed three-dimensional pose of the oralhygiene device, predict a position within the region of interest for apredetermined number of the candidate visual markers; compare thepredicted positions for the predetermined number of the candidate visualmarkers with actual positions of all of the candidate visual markerswithin the region of interest; and responsive to a determination that atleast a substantial portion of the predicted positions correspond withthe actual positions, validate the proposed three-dimensional pose.

According to other implementations of the present disclosure, a motiontracking element configured to be coupled to an oral hygiene deviceincludes a body, a pattern on an outer surface of the body, and aplurality of groups of visual markers on the outer surface of the body.

The above summary of the present disclosure is not intended to representeach embodiment, or every aspect, of the present disclosure. Additionalfeatures and benefits of the present disclosure are apparent from thedetailed description and figures set forth below.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration of a motion tracking system accordingto some implementations of the present disclosure;

FIG. 2A is a perspective view of a tracking element and an oral hygienedevice according to some implementations of the present disclosure;

FIG. 2B is a front view of the tracking element of FIG. 2A;

FIG. 2C is a rear view of the tracking element of FIG. 2A;

FIG. 3 is a flow diagram for a method for estimating a pose of an oralhygiene device relative to a location according to some implementationsof the present disclosure; and

FIG. 4 is a flow diagram illustrating of a step of obtaining a firstproposed three-dimensional pose and a step of validating the firstproposed three-dimensional pose.

While the disclosure is susceptible to various modifications andalternative forms, specific embodiments are shown by way of example inthe drawings and are described in detail herein. It should beunderstood, however, that the disclosure is not intended to be limitedto the particular forms disclosed. Rather, the disclosure is to coverall modifications, equivalents and alternatives falling within thespirit and scope of the disclosure.

DETAILED DESCRIPTION

Referring to FIG. 1, a motion tracking system 100 includes an oralhygiene device 110, a tracking element 120, a camera 130, a processor140, and a memory device 150. The motion tracking system 100 isgenerally used to estimate a pose of the oral hygiene device 110 in athree-dimensional space relative to a location, such as, for example,the camera 130.

The oral hygiene device 110 includes a head 112 and a handle 114. Thehead 112 is coupled to a first end of the handle 114 and includes aplurality of bristles for brushing teeth. The head 112 and the handle114 can be unitary or monolithic or, alternatively, the head 112 can beremovably coupled to the handle 114 such that the handle 114 isinterchangeable (e.g., with a replacement head). The handle 114 has agenerally cylindrical shape, but more generally can be any suitable sizeand shape. The handle 114 can include an ergonomic grip to aid a user ingripping the handle 114. The oral hygiene device 110 can include anelectric motor (not shown) to vibrate and/or oscillate or otherwiseprovide motion to the head 112 to aid in brushing teeth. More generally,the oral hygiene device 110 can be any manual toothbrush or electrictoothbrush.

The tracking element 120 can be detachably coupled (directly orindirectly) to, fixedly or rigidly coupled (directly or indirectly) to,or formed integrally with, the handle 114 of the oral hygiene device110. Further, the tracking element 120 can be coupled to the handle 114of the oral hygiene device 110 such that an axis of the tracking element120 corresponds with or is co-axial with an axis of the handle 114. Thetracking element 120 includes a pattern 122 and a plurality of visualmarkers 124. The tracking element 120 is generally made from a flexiblematerial. For example, the tracking element 120 can be made from anon-conductive material such as, for example, a rubber or elastomermaterial, a polymer material, or any combination thereof.

The camera 130 is a digital camera that is generally used to capturestill images, video images, or both, of at least a portion of the oralhygiene device 110 and the tracking element 120. Typically, the oralhygiene device 110 is positioned between the user 101 and the camera 130such that the field of view of the camera 130 encompasses at least aportion of the oral hygiene device 110 and at least a portion of thetracking element 120.

The processor 140 is communicatively coupled to the camera 130 and thememory device 150. The processor 140 executes instructions (e.g., anassociated application) stored in the memory device 150 to control thevarious components of the system 100 to which it is communicativelycoupled.

In some implementations, the system 100 further includes a housing 160.In such implementations, the camera 130, the processor 140, the memorydevice 150, or any combination thereof can be integrated in the housing160. For example, the housing 160 can be a smartphone. Alternatively,some or all of the various components can be decoupled from one another,and some can be included in a base station (not shown) for the oralhygiene device 110.

Referring to FIGS. 2A-2C, an oral hygiene device 210 that is the same asor similar to the oral hygiene device 110 is coupled to a trackingelement 220 that is the same as or similar to the tracking element 120described above.

The oral hygiene device 210 includes a head (not shown) and a handle214. The head is a coupled to a first end of the handle 214 and thetracking element 220 is coupled to a second end of the handle 214 thatis opposite the head.

The tracking element 220 includes an upper portion 222, a lower portion226, a pattern 230, a first group of visual markers 241, a second groupof visual markers 242, and a third group of visual markers 243. Theupper portion 222 has a generally cylindrical configuration and includesa cavity 224. The cavity 224 is sized and shaped to receive the handle214 of the oral hygiene device 210 therein to removably couple thetracking element 220 to the handle 214 using a press or interferencefit. The upper portion 222 may, for example, be formed from anelastomeric material in the form of a sleeve and be configured andarranged to receive and conform to the second end of the handle 214.Alternatively, the tracking element 220 can be coupled to the handle 214using other mechanisms, such as, for example, a threaded connection, anadhesive connection, a hook and loop fastener, a tab and aperturesystem, a press or interference fit connection, a snap fit connection, aforce fit connection, a twist-lock connection, or the like, or anycombination thereof. Alternatively, in some implementations, thetracking element 220 includes a male attachment feature and the secondend of the handle 214 can include a cavity that is similar to the cavity224 and is sized and shaped to receive at least a portion of the maleattachment feature therein. In such implementations, the trackingelement 220 male attachment feature and the cavity of the handle 214 canbe coupled using any of the fastening mechanisms described above.Advantageously, in this configuration, the tracking element 220 can beremoved from the oral hygiene device 210 if the user does not desire touse the tracking element 220 during a given brushing session. Further,the tracking element 220 can be removed from the oral hygiene device 210and coupled to a second oral hygiene device such as, for example, whenthe user replaces the oral hygiene device 210 at the end of its usefullife or in the event another user desires to use the tracking element220 on another oral hygiene device. Alternatively, the tracking element220 and the handle 214 can be unitary and/or monolithic.

As shown in FIGS. 2A-2C, the lower portion 226 of the tracking element220 can have a generally spherical configuration, although other sizesand shapes are possible. As shown, the pattern 230 formed on an outersurface thereof and is flush with the outer surface of the lower portion226 and includes a background 232 and a plurality of indicators 234.

As shown, each of the plurality of indicators 234 have an amorphousshape that is generally circular-like or oval-like. The shape of theplurality of indicators 234 shown in FIG. 2A-2C is preferable becausethis shape minimizes blur associated with movement of the oral hygienedevice 210 and the tracking element 220 when capturing an image of thesame. Alternatively, one or more of the indicators of the plurality ofindicators 234 can have a generally triangular shape, a generallyrectangular shape, a polygonal shape, or any combination thereof. Whileeach of the plurality of indicators 234 is shown as having the sameshape and size, each of the plurality of indicators 234 can have adifferent size or substantially the same size (e.g., diameter).

Each of the plurality of indicators 234 have a first color and thebackground 232 has a second color that is different than the firstcolor. In one example, the background 232 is an orange color and each ofthe plurality of indicators 234 are a black color. Alternatively, thebackground 232 can be a black color and each of the plurality ofindicators 234 can be a generally orange color, although other colorsfor the background 232 and the plurality of indicators 234 are possible(e.g., red, green, blue, yellow, orange, purple, etc.). In general, ahigh contrast between the color of the background 232 and each of theplurality of indicators 234 is preferable so as to clearly define eachof the plurality of indicators 234. The plurality of indicators 234defining the pattern 230 on the tracking element 220 can have betweenabout ten indicators and about one hundred indicators, between abouttwenty indicators and about sixty indicators, between about thirty-fiveand about forty-five indicators, or any suitable number of indicators.

The plurality of indicators 234 and the background 232 of the pattern230 can be formed using a variety of mechanisms. For example, at leastsome of the plurality of indicators 234 and/or the background 232 of thepattern 230 can be printed or embossed on the outer surface of thetracking element 220. Alternatively, at least some of the plurality ofindicators 234 and/or the background 232 can be integral with the lowerportion 226.

Referring to FIGS. 2A-2C, the first group of visual markers 241, thesecond group of visual markers 242, and the third group of visualmarkers 243 are coupled to the outer surface of the lower portion 226and protrude therefrom. As shown, each visual marker in the groups ofvisual markers 241, 242, 243 has a generally ovoid, dome-like orsemi-spherical shape. The first, second, and third groups of visualmarkers 241, 242, 243 can be coupled to the outer surface of the lowerportion 226 using an adhesive connection, for example, or more generallyany other suitable mechanism. Alternatively, each of the visual markerscan be unitary and/or monolithic with the lower portion 226 of thetracking element 220.

Referring to FIGS. 2B and 2C, the first group of visual markers 241includes a first visual marker 241 a, a second visual marker 241 b, athird visual marker 241 c, and a fourth visual marker 241 d. The handle214 has a front surface 214 a and a rear surface 214 b. The cleaningelements (e.g., bristles) on the head (not shown) extend from the frontsurface 214 a of the handle 214. To illustrate all of the visualmarkers, FIG. 2B is a front view of the oral hygiene device 210 (i.e.,includes the front surface 214 a) and FIG. 2C is a rear view the oralhygiene device 210 (i.e., includes the rear surface 214 b).

In some implementations, the first group of visual markers 241 extendsalong a first circumferential length of the lower portion 226 that isproximate to the upper portion 222 and the handle 214. As shown, each ofthe visual markers in the first group of visual markers 241 are evenlyspaced from one another along the first circumferential length.

The second group of visual markers 242 includes a first visual marker242 a, a second visual marker 242 b, a third visual marker 242 c, and afourth visual marker 242 d. The second group of visual markers 242extends along a second circumferential length of the lower portion 226that is spaced from the first circumferential length. As shown, each ofthe visual markers in the second group of visual markers 242 are evenlyspaced from one another along the first circumferential length, butoffset circumferentially from the visual markers in the first group ofvisual markers 241. Specifically, the first visual marker 242 a ispositioned between the first visual marker 241 a and the second visualmarker 241 b of the first group of visual markers 241 (FIG. 2B), thesecond visual marker 242 b is positioned between the second visualmarker 241 b and the third visual marker 241 c of the first group ofvisual markers 241 (FIG. 2B), the third visual marker 242 c ispositioned between the third visual marker 241 c and the fourth visualmarker 241 d of the first group of visual markers 241 (FIG. 2C), and thefourth visual marker 242 d is positioned between the fourth visualmarker 241 d and the first visual marker 241 a of the first group ofvisual markers 241 (FIG. 2D).

The third group of visual markers 243 includes a first visual marker 243a, a second visual marker 243 b, a third visual marker 243 c, and afourth visual marker 243 d. The third group of visual markers 243extends along a third circumferential length of the lower portion 226that is spaced from the second circumferential length and distal to theupper portion 222 and the handle 214. The first circumferential length,the second circumferential length, and the third circumferential lengthare evenly spaced from one another such that the first group of visualmarkers 241, the second group of visual markers 242, and the third groupof visual markers 243 are evenly spaced from one another.

The third group of visual markers 243 includes a first visual marker 243a, a second visual marker 243 b, a third visual marker 243 c, and afourth visual marker 243 d. The first visual marker 243 a is alignedwith the first visual marker 241 a of the first group of visual markers241 such that the first visual marker 243 a is positioned between thefourth visual marker 242 d and the first visual marker 242 a of thesecond group of visual markers 242. The second visual marker 243 b isaligned with the second visual marker 241 b of the first group of visualmarkers 241 such that the second visual marker 243 b is positionedbetween the first visual marker 242 a and the second visual marker 242 bof the second group of visual markers 242. The third visual marker 243 cis aligned with the third visual marker 241 c of the first group ofvisual markers 241 such that the third visual marker 243 c is positionedbetween the second visual marker 242 b and the third visual marker 242 cof the second group of visual markers 242. The fourth visual marker 243d is aligned with the fourth visual marker 241 d of the first group ofvisual markers 241 such that the fourth visual marker 243 d ispositioned between the third visual marker 242 c and the fourth visualmarker 242 d of the second group of visual markers 242.

Each of the visual markers within the first group of visual markers 241,the second group of visual markers 242, and the third group of visualmarkers 243 has a distinctive color. For example, in the first group ofvisual markers 241, the first visual marker 241 a has a first color, thesecond visual marker 241 b has a second color, the third visual marker241 c has a third color, and the fourth visual marker 241 d has a fourthcolor. The first color, the second color, the third color, and thefourth color are all different from one another. Preferably, the firstcolor, second color, third color, and fourth color are separate anddistinct colors that are spaced out along the color spectrum. Forexample, each color can be spaced from the other colors by between abouta 150 nm wavelength to a 15 nm wavelength in the color spectrum, about a100 nm wavelength in the color spectrum to about a 25 nm wavelength inthe color spectrum, or about a 75 nm wavelength in the color spectrum toabout a 50 nm wavelength in the color spectrum, or the like. Forexample, the first color, second color, third color, and fourth colorcan be a blue color, a green color, a purple color, a yellow color, ared color, or an orange color, which are spread out substantiallyequally along the color spectrum.

In one example, referring to the first group of visual markers 241, thefirst visual marker 241 a is a purple color, the second visual marker241 b is a blue color, the third visual marker 241 c is a yellow color,and the fourth visual marker 241 d is a green color. Referring to thesecond group of visual markers 242, the first visual marker 242 a is ayellow color, the second visual marker 242 b is a green color, the thirdvisual marker 241 c is a blue color, and the fourth visual marker 241 dis a purple color. Referring to the third group of visual markers 243,the first visual marker 243 a is a green color, the second visual marker243 b is a purple color, the third visual marker 243 c is a blue color,and the fourth visual marker 243 d is a yellow color. In thisconfiguration, each of the four colors (blue, green, purple, and yellow)are evenly distributed and spaced from one another among the groups ofvisual markers. For example, a yellow visual marker is not directlyadjacent to another yellow visual marker and a blue visual marker is notdirectly adjacent to another blue visual marker.

In this example described above, there are three purple visual markers,three blue visual markers, three yellow visual markers, and three greenvisual markers (i.e., markers with four different colors). While each ofthe first group of visual markers 241, the second group of visualmarkers 242, and the third group of visual markers 243 is shown asincluding four visual markers, more generally, the attachment 220 caninclude any number of groups of visual markers including at least onevisual marker. For example, the attachment 220 can include a first groupof visual markers, a second group of visual markers, a third group ofvisual markers, and a fourth group of visual markers, with each groupcontaining at least one visual marker. Further, the at least one visualmarker in each group has a different color than the visual markers inthe other groups. Further, while the attachment 220 (FIGS. 2A-2B) isshown as including twelve visual markers combined between the firstgroup 241, the second group 242, and the third group 243, it should beunderstood that the attachment 220 can include any number of visualmarkers (e.g., four visual markers, six visual markers, ten visualmarkers, twenty visual markers, fifty visual markers, etc.) having fouror more different colors (e.g., four different colors, six differentcolors, ten different colors, twenty different colors, etc.). As will bediscussed in more detail herein, having four or more visual markershaving different colors is preferable to accurately and efficientlytrack motion of the tracking element 220. Further, while the first groupof visual markers 241, the second group of visual markers 242, and thethird group of visual markers 243 are each positioned along acircumferential length of the lower portion 226 and are evenly spacedfrom one another, the visual markers can be positioned relative to oneanother in any appropriate arrangement (e.g., randomly) on the outersurface of the lower portion 226.

Referring to FIG. 3, a method 300 for estimating a pose of the oralhygiene device 210 relative to a location includes, for example, a firststep 310, a second step 320, a third step 330, a fourth step 340, afifth step 350, and a sixth step 360.

The first step 310 includes receiving image data, from a camera that isthe same as or similar to the camera 130 (FIG. 1) described above, thatis reproducible as an image of at least a portion of the oral hygienedevice 210 and at least a portion of the tracking element 220. Forexample, the image data can be a frame of a video image captured by thecamera. As described above, the camera is positioned relative to theuser (e.g., user 101) such that the oral hygiene device 210 and thetracking element 220 are positioned between the camera and the user.Because the field of view of the camera encompasses the oral hygienedevice 210, the tracking element 220, and at least a portion of theuser, the captured video or still image includes at least a portion ofall three and the background behind the user that is within the field ofview of the camera.

The second step 320 includes analyzing the image data from the firststep 310 to identify a region of interest within the image. Generally,the region of interest is an area of the image received during the firststep 310 that includes the tracking element 220. As described above, theimage captured during the first step 310 includes at least a portion ofthe user and a background behind the user. By limiting the region ofinterest to an area surrounding the tracking element 220, the processingrequirements for the subsequent steps of the method 300 can be reduced.

To analyze the image data and identify the region of interest, one ormore processors that are the same as or similar to the processor 140(FIG. 1) described above are used to identify the pattern 230 of thetracking element 220 (FIG. 2A) using a plurality of filters. Theplurality of filters includes a movement filter, a color filter, and ashape filter. The movement filter detects or identifies movement withinthe image. Generally, the movement filter detects movement bydistinguishing areas of movement in the image compared to stationaryareas of the image. The movement filter takes advantage of the fact thatthe pattern 230 is likely to be moving due to corresponding movement ofthe oral hygiene device 210 and the tracking element 220 to narrow thepotential area(s) of the image that could be the region of interest(i.e., contain at least a portion of the pattern 230) by eliminating thestationary background of the image. The color filter and the shapefilter identify the contrast in color between the background 232 and theplurality of indicators 234 and the shape of each of the plurality ofindicators 234. Having detected an area of the image containing thepattern 230, the region of interest is defined as that area and excludesthe remainder of the image.

Identifying the region of interest in a high resolution or highdefinition image requires substantial processing/computation time. Toreduce the processing requirements for identifying the region ofinterest, the image analyzed during the second step 320 is preferably alow resolution image. The region of interest can then be upscaled to ahigher resolution image for the remainder of the steps of the method300.

In some implementations, the pattern 230 of the tracking element 220 canbe filtered or detected to identify the region of interest using amachine learning algorithm or an artificial intelligence algorithm.Machine learning algorithms may take a variety of forms. For example,the method 300 can utilize more basic machine learning tools such as adecision tree (“DT”) or an artificial neural network (“ANN”). DTprograms are generally used because of their simplicity and ease ofunderstanding. DT are classification graphs that match input data toquestions asked at each consecutive step in a decision tree. The DTprogram moves down the “branches” of the tree based on the answers tothe questions. For example, a first branch may ask if a portion of theimage is moving. If yes, a second branch may ask whether the portion ofthe image includes the pattern 230. In other examples, deep learningalgorithms or other more sophisticated machine learning algorithms canbe used, such as, for example, a convolutional neural network.

Machine learning algorithms (e.g., a Haar Cascade) require training datato identify the features of interest that they are designed to detect.For instance, various methods may be utilized to form the machinelearning models including applying randomly assigned initial weights forthe network and applying gradient descent using back propagation fordeep learning algorithms. In other examples, a neural network with oneor two hidden layers can be used without training using this technique.In some examples, the machine learning algorithms will be trained usinglabeled data, or data that represents certain features, specificactions, or characteristics, including a particular color or aparticular shape.

The third step 330 includes identifying candidate visual markers in theregion of interest identified during the second step 320. Generally,candidate visual markers are sub-regions of the region of interest thatcould be an actual visual marker (e.g., one of the visual markers of thegroups of visual markers 241, 242, or 243 in FIGS. 2A-2C) on thetracking element 220. To identify candidate visual markers, the regionof interest is segmented in a plurality of sub-regions using a colorsegmentation algorithm. Each sub-region is defined by a plurality ofpixels of the region of interest that have a common color.

Generally, the color segmenting algorithm assumes that objects arecolored distinctively and seeks to identify gross color differencesbetween adjacent pixels in an image. The color segmenting algorithm usesthe L*a*b color space, which defines colors in terms of luminosity(“L”), where the color falls along the red-green axis (“*a”), and wherethe color falls along the blue-yellow axis (“*b”). As a result, ifnecessary, the region of interest identified in the second step 320 isconverted from a RGB color space to the L*a*b color space to perform thecolor segmenting algorithm. Using a threshold value, the colorsegmenting algorithm separates adjacent pixels having distinctive colorsfrom one another to form a plurality of sub-regions. The average colorin the L*a*b color space of each of the plurality of sub-regions is thencalculated.

As discussed above, the color of the visual markers in the first group241, the second group 242, and the third group 243 preferably is one ofblue, green, purple, yellow color, red, or orange. Thus, a sub-region ofthe region of interest having a blue, green, purple, or yellow colorcould be a candidate visual marker. While the region of interest islimited to an area encompassing the tracking element 220, the region ofinterest may still include a portion of the user or the backgroundbehind the user, which can create false positive for a candidate visualmarker. For example, the user may be wearing clothing which has one ormore of the same or similar colors as the visual markers.

To increase the accuracy of identifying candidate visual markers, thethird step 330 also includes a shape filter and a size filter. Thevisual markers of the first group of visual markers 241, the secondgroup of visual markers 242, and the third group of visual markers 243(FIGS. 2A-2C) have a generally dome-like or hemispheric shape. Whenviewed in a two-dimensional image such as the region of interest, thesevisual markers have a generally circular shape. The shape filter and thesize filter are used to detect the generally circular shape of thevisual markers within the region of interest. These filters aid indiscriminating between a visual marker and, for example, the clothing ofthe user.

The fourth step 340 includes obtaining a first proposedthree-dimensional pose of the oral hygiene device 210. Generally, thefirst proposed three-dimensional pose includes the position andorientation (rotation and translation) of the oral hygiene device 210relative to the camera. As will be discussed in more detail herein, insome implementations, the fourth step 340 will not initialize until atleast four candidate visual markers are identified during the third step330. If less than four candidate visual markers are identified duringthe third step 330, the method 300 is repeated until at least fourcandidate visual markers are identified.

Referring to FIG. 4, the fourth step 340 includes a first sub-step 342,a second sub-step 348, a third sub-step 348, and a fourth sub-step 348.

The first sub-step 342 includes grouping the candidate visual markersidentified during the third step 330 (FIG. 3) into discrete sets ofcandidate visual markers. Preferably, each of the discrete sets ofcandidate visual markers includes four candidate visual markers.

Similarly, the second sub-step 348 includes grouping model markers froma three-dimensional model of the oral hygiene device 210 and thetracking element 220 into discrete steps. The three-dimensional model isstored in a memory device that is the same as or similar to the memorydevice 150 described above (FIG. 1). The three-dimensional model is arepresentation of the actual oral hygiene device 210 and the trackingelement 220. Specifically, the three-dimensional model includesrepresentations of the first group of visual markers 241, the secondgroup of visual markers 242, and the third group of visual markers 243.The number of model markers in each of the discrete sets of modelmarkers is equal to the number of candidate visual markers in the firstdiscrete set of candidate visual markers grouped together during thefirst step 342 (e.g., four candidate visual markers and four modelmarkers).

The third sub-step 348 includes selecting a first discrete set ofcandidate visual markers and a first discrete set of model markers. Thefirst discrete set of candidate visual markers includes four visualmarkers and the first discrete set of model markers includes four modelmarkers.

The fourth sub-step 348 includes inputting the first discrete set ofcandidate visual markers and the first discrete set of model markersselected during the third sub-step 348 into a perspective-three-point(“P3P”) algorithm. The P3P algorithm is based on the law of cosines andis used to estimate an object pose (a rotation and translation) relativeto the camera placement.

Generally, the P3P algorithm compares two-dimensional points taken froman image with three-dimensional points taken from a three-dimensionalmodel. To solve the P3P equation system, four two-dimensional pointsdefined in an image coordinate system and four three-dimensional pointsdefined in a three-dimensional model coordinate system are provided.Three sets of points, each set including a two-dimensional point and athree-dimensional point, are used to solve the P3P equation system anddetermine up to four possible sets of distances between thetwo-dimensional points and the optical center of the camera. These foursets of distances are converted into four pose configurations. Thefourth set of 2D/3D points is then used to select the best or mostcorrect pose configuration against the four proposals. There are variousmethods for solving the P3P equation system and obtaining an estimatedthree-dimensional pose. For example, one such method is explained inLaurent Kneip et. al, A Novel Parametrization of thePerspective-Three-Point Problem for a Direct Computation of AbsoluteCamera Position and Orientation, The IEEE Conference on Computer Visionand Pattern Recognition (CVPR), June 2011), which is hereby incorporatedby reference in its entirety.

Inputting the first discrete set of candidate visual markers and thefirst discrete set of model markers into the P3P algorithm and solvingthe equation system yields a first proposed three-dimensional pose ofthe oral hygiene device 210. The first proposed three-dimensional poseincludes a rotational and a translational position of the oral hygienedevice 210 that permits the position of the oral hygiene device 210relative to the camera to be determined. As discussed above, in someimplementations, the fourth step 340 will not initialize until fourcandidate visual markers are identified during the third step 330. Thisis because solving the P3P algorithm requires four candidate visualmarkers and four model markers. If less than four candidate visualmarkers are identified in the third step 330, the P3P algorithm equationsystem generally cannot be solved without more data.

The fifth step 350 (FIG. 3) includes validating the first proposedthree-dimensional pose of the oral hygiene device 210 determined duringthe fourth step 340. It is possible that the first discrete set ofcandidate visual markers and the first discrete set of model markersselected in sub-step 348 yield a proposed three-dimensional pose that isincorrect (e.g., a pose that is not physically possible). Thus, thefifth step 350 is generally used to validate or reject the proposedthree-dimensional pose obtained during the fourth step 340.

Referring to FIG. 4, the fifth step 350 includes a first sub-step 352, asecond sub-step 354, a third sub-step 356, and a fourth sub-step 358.The first sub-step 352 includes predicting the positions of thecandidate visual markers within the region of interest. Based on thefirst proposed three-dimensional pose calculated during the fourth step340, and the known positions of visual markers from thethree-dimensional model of the oral hygiene device 210 and the trackingelement 220, the position of the visual markers within the region ofinterest can be predicted. In other words, the predicted positionsindicate where candidate visual markers should be located in the regionof interest if the first proposed three-dimensional pose is correct, andwhere candidate visual markers should not be located. For example, itmay be predicted that six visual markers will be visible in the regionof interest if the oral hygiene device 210 has the same pose as thefirst proposed three-dimensional pose. The position of these six visualmarkers relative to one another in the region of interest is determinedfrom the three-dimensional model of the oral hygiene device.

The second sub-step 354 includes comparing the candidate visual markersidentified in the region of interest with the predicted positions of thevisual markers. More specifically, the number and position of thecandidate visual markers is compared to the predicted number andpredicted position of the visual markers (first sub-step 354 of thefifth step 350). If it is determined that the positions of apredetermined number of the candidate visual markers correspond to thepredicted positions, the first proposed three-dimensional pose isvalidated (sub-step 356). If less than the predetermined number ofcandidate markers correspond to the predicted positions, the firstproposed three-dimensional pose is rejected (sub-step 358).

To illustrate by way of an example, the first sub-step 352 predicts thatsix candidate visual markers will be visible in the region of interest,and predicts the position of each of these six candidate visual markersrelative to one another. The third step 330 identified ten candidatevisual markers within the region of interest. If, for example, acandidate visual marker corresponds to five of the six predicted visualmarkers, the first proposed three-dimensional pose is validated(sub-step 356) and the fifth step 350 is completed. The other fourcandidate visual markers are simply considered to be noise orinaccurate. Alternatively, if there are thirty candidate visual markersidentified during the third step 330, and for example, twenty-five ofthe thirty do not correspond to a predicted position, the proposedthree-dimensional pose may be rejected.

The predetermined number of correspondences required to validate aproposed three-dimensional pose can be expressed as a percentage, andcan be at least about 50% of the predicted positions of the visualmarkers correspond to positions of candidate visual markers, at leastabout 60% of the predicted positions of the visual markers correspond topositions of candidate visual markers, at least about 70% of thepredicted positions of the visual markers correspond to position ofcandidate visual markers, at least about 80% of the predicted positionsof the visual markers correspond to positions of candidate visualmarkers, at least about 90% of the predicted positions of the visualmarkers correspond to positions of candidate visual markers, or 100% ofthe predicted positions of the visual markers correspond to positions ofcandidate visual markers). In some implementations, the predeterminednumber is a statistically significant number such that it can bedetermined that the first proposed three-dimensional pose is correctwith a suitable statistical certainty (e.g., 95% statistical certainty,85% statistical certainty, 75% statistical certainty, etc.).

If the first proposed-three dimensional pose is rejected (sub-step 358),the second sub-step 348 (FIG. 4) of the fourth step 340 is repeated.During the repeating of the sub-step 348, a second discrete set ofcandidate visual markers and a second discrete set of model markers areselected. At least one of the second discrete set of candidate visualmarkers and the second discrete set of models markers includes a set ofcandidate visual markers or model markers that is different from thefirst discrete set of candidate visual markers and/or the seconddiscrete set of model markers. These sets are then inputted into the P3Palgorithm in sub-step 348 to obtain a second proposed three-dimensionalpose of the oral hygiene device 210. The second proposedthree-dimensional pose is then validated or rejected during the fifthstep 350. Steps 348 through 354 are repeated until a proposedthree-dimensional pose is validated (sub-step 356).

During the repeating of the steps described above to validate a proposedthree-dimensional pose, numerous discrete sets of candidate visualmarkers and discrete sets of model markers may be inputted into the P3Palgorithm until a proposed pose is validated. Because there are twelvevisual markers collectively between the first group of visual markers241 in the example shown in FIGS. 2A-2C, the second group of visualmarkers 242, and the third group of visual markers 243 (FIGS. 2A-2C),there are 469 possible combinations of four visual markers if the colorof the visual markers is disregarded. In other words, there are 469possible discrete sets of four model markers. If for example, there aresixteen candidate visual markers identified in the region of interest(during step 330), disregarding color, there are 1,820 combinations offour candidate visual markers (i.e., 1,820 possible discrete sets ofcandidate visual markers). This means that there is potentially over900,000 proposed three-dimensional poses that may be determined beforeone is validated, requiring substantial processing/computation time.However, as described above, each of the first group of visual markers241, the second group of visual markers 242, and the third group ofvisual markers 243 includes four visual markers, and each of the fourvisual markers in each group has a different color. The grouping ofcandidate visual markers and model markers can then be furtherconditioned such that each group not only is limited to four visualmarkers, but each visual marker in the group of four has a differentcolor. In this manner, the number of possible combinations that may needto be inputted into the P3P algorithm (sub-step 348) before validating aproposed three-dimensional pose (sub-step 356) is reduced from, forexample, the hundreds of thousands to several hundred. This reduces theprocessing/computational requirements such that the method can beimplemented on, for example, a smartphone with limited processing power.

The sixth step 360 includes obtaining a second proposedthree-dimensional pose of the oral hygiene device 210 based on thevalidated first proposed three-dimensional pose of the oral hygienedevice 210. The second proposed three-dimensional pose of the oralhygiene device 210 is calculated in a similar manner as the firstproposed three-dimensional pose during the fifth step 350. As discussedabove, during the first sub-step 352 of the fifth step 350, thepositions of each of the visual markers in the region of interest arepredicted. As also discussed above, there may be a greater number ofcandidate visual markers identified during the third step 330 than theamount of predicted visual markers due to noise from the background orinaccuracy involved in the color segmenting algorithm. To obtain a morerefined pose estimation, the sixth step 360 selects only the candidatevisual markers (“correct candidate visual markers”) that correspond topredicted visual markers, ignoring candidate visual markers that areincorrect based on the predicted positions. These correct candidatevisual markers are then compared to model markers from thethree-dimensional model of the oral hygiene device 210 using aniterative pose estimation algorithm and linear regressions to obtain asecond proposed three-dimensional pose of the oral hygiene device 210.The second proposed three-dimensional pose of the oral hygiene device210 is generally more accurate than the first proposed three dimensionalpose (fourth step 340), but requires more processing/computation time todetermine.

Referring to FIG. 3, after completion of the sixth step 360, the method300 can be repeated one or more times. In a second iteration of themethod 300, the first step 310 is repeated and includes receiving imagedata that is reproducible as a second image of at least a portion of theoral hygiene device 210 and the tracking element 220. For example, thesecond image can be a second frame of a video image that is takensubsequent to the image used during the initial iteration of the method300.

The second step 320 is then repeated to identify a second region ofinterest in the second image received during the first step 310.However, in the second iteration of the method 300, detection of thepattern 230 of the tracking element 220 to identify the region ofinterest is bypassed. Instead the second region of interest is selectedusing the second three-dimensional pose estimation (sixth step 360), andthe second region of interest is defined an area of the second image inwhich at least a portion of the tracking element 220 is positioned.Because the second step 320 in the second iteration of the method 300does not require detection of the pattern 230 using a plurality offilters, the required processing/computation time to complete the secondstep 320 is reduced.

The third step 330 is then repeated to identify all of the candidatevisual markers in the second region of interest using the colorsegmenting algorithm described above. Typically, the oral hygiene device210 will be used in a bathroom that may have bright or intense lighting,which can be further amplified by reflections in a bathroom mirror.Further, movement of the oral hygiene device 210 may cause the lightingconditions in the region of interest to change based on position of theoral hygiene device relative to a light source (e.g., the user may casta shadow on a portion of the oral hygiene device 210 in a particularpose). The lighting conditions and/or movement of the oral hygienedevice 210 may affect the amount of light reflecting off of the visualmarkers of the tracking element 220. For example, it may be difficult todiscern a blue color from a purple under intense or bright lightingconditions or dark lighting conditions. By using the secondthree-dimensional pose estimation obtained during the sixth step 360,the threshold for distinguishing colors in the color segmentingalgorithm can be adjusted based on the three-dimensional pose estimationobtained in the sixth step 360 of the first iteration of the method 300.This threshold is then updated each time the third step 330 is completedas the method 300 is repeated.

The fourth step 340, the fifth step 350, and the sixth step 360 are thenrepeated in the same or similar manner as described above to obtainanother second three-dimensional pose estimation of the oral hygienedevice 210.

Steps 310 through 360 can then be repeated a plurality of times (e.g.,ten times, fifty times, one hundred times, one thousand times, etc.)after the second iteration described above description to track motionof the oral hygiene device 210. The sixth step 360 will output a seriesof estimated three-dimensional poses of the oral hygiene device 210 asthe method 300 is repeated, which can be then used to track the movementof the oral hygiene device 210 over time. This repeating of the method300 can be used to track the motion of the oral hygiene device 210during, for example, a brushing session in which a user is brushingtheir teeth. Data relevant to the quality of brushing by a user or theoverall dental health of the user's teeth can be collected and analyzedbased on the motion data. For example, a brush stroke type (e.g., aside-to-side stroke, an angular stroke, or a circular stroke) can bedetermined.

In some implementations, the system 100 can also be utilized todetermine the position and orientation of a face of a user. For example,using the camera 104, the system 100 receives an image of at least aportion of the face of the user. Using the processor 140 and the memory150 and a facial recognition algorithm, the position and orientation ofthe face can be determined. For example, the system 100 may determinethe position of the user's eyes, mouth, or nose (or any combinationthereof) using, for example, a plurality of filters, machine-learningalgorithms, or the like. In one example, the position of the user'smouth can be estimated based on the position of the user's eyes and adistance between the eyes and mouth of the user.

By determining the position and orientation of the face of the user, theposition of the oral hygiene device 210 can be determined not only withrespect to the camera, but to the mouth of the user. Thus, the positionof the oral hygiene device relative to the teeth of the user and thusdetermine and whether a user has a brushed a certain section of teethcan be determined.

In some implementations, the method 300 further includes an initialcalibration step to determine the rotational position of the trackingelement 220 relative to the oral hygiene device 210. For example, usingthe techniques described above, the calibration step can initiallydetermine the rotational position of the tracking element 220 on theoral hygiene device 210 and communicate that position to adjust thethree-dimensional model so that the rotational position of the trackingelement 220 in the three-dimensional model corresponds with therotational position on the actual oral hygiene device 210. In otherimplementations, the method 300 is agnostic to how the tracking element220 is coupled to the handle 214 of the oral hygiene device 210.

Advantageously, the tracking element 220 can be used to track motion ofthe oral hygiene device 210 using the method 300 (or other similarmethods) without requiring any electronics or sensors (e.g., anaccelerometer) in the tracking element 220. While the tracking element220 can include such sensors in some implementations to aid in trackingmotion of the oral hygiene device 210, such sensors may, for example,increase the cost of the tracking element 220, require the trackingelement 220 to be charged periodically prior to use, or increase theweight of the tracking element 220 and thus interfere with a user's(e.g., a child's) brushing given the added weight at the end of the oralhygiene device 210.

While the system 100 and method 300 have been illustrated and describedherein as being used to track the motion of an oral hygiene device(e.g., oral hygiene device 210), the system 100 and method 300 can beused to track the motion of any other object coupled to the trackingelement 220. For example, a tracking element that is the same as orsimilar to the tracking element 220 can be coupled to an end of anobject with a similar shape as the oral hygiene device 210, such as, forexample, a baseball bat, a hockey stick, a golf club, or the like.Further, a tracking element that is similar to the tracking element 220can more generally be attached to an object with any other shape totrack the motion of the object.

While the disclosure is susceptible to various modifications andalternative forms, specific embodiments and methods thereof have beenshown by way of example in the drawings and are described in detailherein. It should be understood, however, that it is not intended tolimit the disclosure to the particular forms or methods disclosed, but,to the contrary, the intention is to cover all modifications,equivalents and alternatives falling within the spirit and scope of thedisclosure.

SELECTED EMBODIMENTS

Although the above description and the attached claims disclose a numberof embodiments, other alternative aspects of the present disclosure aredisclosed in the following further embodiments.

Embodiment 1

A method for estimating a pose of an oral hygiene device relative to alocation, the oral hygiene device including a pattern and a plurality ofgroups of visual markers, the method comprising: receiving image datareproducible as an image of at least a portion of the oral hygienedevice; analyzing, using one or more processors, the image data toidentify a region of interest within the image, the region of interestincluding at least a portion of the pattern therein; identifying, usingat least one of the one or more processors, all candidate visual markerswithin the region of interest; obtaining a first proposedthree-dimensional pose of the oral hygiene device; validating the firstproposed three-dimensional pose of the oral hygiene device; obtaining asecond proposed three-dimensional pose of the oral hygiene device basedon the validated first proposed three-dimensional pose.

Embodiment 2

The method of embodiment 1, wherein responsive to identifying the regionof interest, segmenting, using at least one of the one or moreprocessors, the region of interest into a plurality of sub-regions, eachof the plurality of sub-regions being defined by a plurality of pixelshaving a common color.

Embodiment 3

The method according to any one of embodiments 1 and 2, wherein theobtaining the first proposed three-dimensional pose of the oral hygienedevice includes: creating a plurality of distinct sets of the candidatevisual markers; selecting a first one of the plurality of distinct setsof the candidate visual markers; selecting a first one of a plurality ofdistinct sets of model markers associated with a three-dimensional modelof the oral hygiene device; and evaluating a set of the candidate visualmarkers and a set of model markers from a three-dimensional modelassociated with the oral hygiene device using a perspective-three-pointalgorithm to obtain the proposed three-dimensional pose of the oralhygiene device.

Embodiment 4

The method according to any one of embodiments 1-3, wherein thevalidating the first proposed three-dimensional pose includes: based onthe proposed three-dimensional pose of the oral hygiene device,predicting a position within the region of interest for a predeterminednumber of the candidate visual markers; and comparing the predictedpositions for the predetermined number of the candidate visual markerswith actual positions of all of the candidate visual markers within theregion of interest; and determining that at least a substantial portionof the predicted positions correspond with the actual positions.

Embodiment 5

The method according to any one of embodiments 1-4, wherein theanalyzing the first image data includes using one or more filters, theone or more filters including a movement filter, a color filter, a shapefilter, or any combination thereof.

Embodiment 6

The method according to any one of embodiments 1-5, wherein theidentifying all candidate visual markers is based on a shape and a colorof each of the plurality of sub-regions.

Embodiment 7

The method according to any one of embodiments 1-6, wherein each of theplurality of distinct sets of the candidate visual markers includes atleast four candidate visual markers and each of the plurality ofdistinct sets of the model markers includes at least four model markers.

Embodiment 8

The method according to any one of embodiments 1-7, further comprising:receiving a second set of image data reproducible as a second image ofat least a portion of the oral hygiene device; identifying a secondregion of interest within the second image based on the validatedthree-dimensional pose of the oral hygiene device.

Embodiment 9

The method according to any one of embodiments 1-8, further comprising:adjusting, based on the validated three-dimensional pose of the oralhygiene device, a threshold for segmenting the second region of interestto aid in identifying pixels having different colors in the secondregion of interest.

Embodiment 10

A method for estimating a pose of an oral hygiene device relative to alocation, the oral hygiene device including a pattern and a plurality ofgroups of visual markers, the method comprising: (a) receiving imagedata reproducible as an image of at least a portion of the oral hygienedevice; (b) analyzing, using one or more processors, the image data toidentify a region of interest within the image, the region of interestincluding at least a portion of the pattern therein; (c) responsive toidentifying the region of interest, segmenting, using at least one ofthe one or more processors, the region of interest into a plurality ofsub-regions, each of the plurality of sub-regions being defined by aplurality of pixels having a common color; (d) identifying, using atleast one of the one or more processors, all candidate visual markerswithin the region of interest; (e) creating a plurality of distinct setsof the candidate visual markers; (f) selecting a first one of theplurality of distinct sets of the candidate visual markers; (g)selecting a first one of a plurality of distinct sets of model markersassociated with a three-dimensional model of the oral hygiene device;(h) evaluating the selected set of the candidate visual markers and theselected set of model markers using a perspective-three-point algorithmto obtain a proposed three-dimensional pose of the oral hygiene device;(i) based on the proposed three-dimensional pose of the oral hygienedevice, predicting a position within the region of interest for apredetermined number of the candidate visual markers; (j) comparing thepredicted positions for the predetermined number of the candidate visualmarkers with actual positions of all of the candidate visual markerswithin the region of interest; (k) responsive to a determination that atleast a substantial portion of the predicted positions correspond withthe actual positions, validating the proposed three-dimensional pose;and (l) responsive to a determination that less than the substantialportion of the predicted positions correspond with the actual positions,repeating steps (f)-(k).

Embodiment 11

The method according to any one of embodiment 10, further includingresponsive to the proposed three-dimensional pose being validated,comparing all of the candidate visual markers and all of the modelmarkers using an algorithm to obtain a second proposed three-dimensionalpose of the oral hygiene device.

Embodiment 12

The method according to any one of embodiments 10 and 11, wherein theanalyzing the first image data includes using one or more filters, theone or more filters including a movement filter, a color filter, a shapefilter, or any combination thereof.

Embodiment 13

The method according to any one of embodiments 10-12, wherein theidentifying all candidate visual markers is based on a shape and a colorof each of the plurality of sub-regions.

Embodiment 14

The method according to any one of embodiments 10-13, wherein each ofthe plurality of distinct sets of the candidate visual markers includesat least four candidate visual markers and each of the plurality ofdistinct sets of the model markers includes at least four model markers.

Embodiment 15

The method according to any one of embodiments 10-14, furthercomprising: receiving a second set of image data reproducible as asecond image of at least a portion of the oral hygiene device;identifying a second region of interest within the second image based onthe validated three-dimensional pose of the oral hygiene device.

Embodiment 16

The method according to any one of embodiment 15, further comprising:adjusting, based on the validated three-dimensional pose of the oralhygiene device, a threshold for segmenting the second region of interestto aid in identifying pixels having different colors in the secondregion of interest.

Embodiment 17

A motion tracking system comprising: an oral hygiene device including ahead and a handle; a tracking element coupled to the oral hygiene deviceincluding a pattern and a plurality of groups of visual markers; acamera; one or more processors; and a memory device storing instructionsthat, when executed by at least one of the one or more processors causethe motion tracking system to, capture, using the camera, an image of atleast a portion of the oral hygiene device; analyze, using at least oneof the one or more processors, the image to identify a region ofinterest within the image, the region of interest including at least aportion of the pattern of the tracking element therein; identify, usingat least one of the one or more processors, all candidate visual markerswithin the region of interest; create a plurality of distinct sets ofthe candidate visual markers; select a first one of the plurality ofdistinct sets of the candidate visual markers; select a first one of aplurality of distinct sets of model markers associated with athree-dimensional model of the oral hygiene device stored in the memorydevice; evaluate the selected set of the candidate visual markers andthe selected set of model markers using a perspective-three-pointalgorithm to obtain a proposed three-dimensional pose of the oralhygiene device; based on the proposed three-dimensional pose of the oralhygiene device, predict a position within the region of interest for apredetermined number of the candidate visual markers; compare thepredicted positions for the predetermined number of the candidate visualmarkers with actual positions of all of the candidate visual markerswithin the region of interest; and responsive to a determination that atleast a substantial portion of the predicted positions correspond withthe actual positions, validate the proposed three-dimensional pose.

Embodiment 18

The system according to any one of embodiment 17, wherein the trackingelement includes a cavity for receiving a portion of the handle of theoral hygiene device therein.

Embodiment 19

The system according to any one of embodiments 17 and 18, wherein thepattern of the tracking element is flush with an outer surface of thetracking element and the plurality of groups of visual markers protrudefrom the outer surface of the tracking element.

Embodiment 20

The system according to any one of embodiment 19, wherein the visualmarkers of each of the plurality of groups of visual markers have agenerally dome-like shape.

Embodiment 21

The system according to any one of embodiments 17-20, wherein thepattern of the tracking element includes a background having a firstcolor and a plurality of indicators overlaid on the background, theplurality of indicators having a second color that is different from thefirst color.

Embodiment 22

The system according to any one of embodiments 17-21, wherein a firstgroup of the plurality of groups of visual markers includes a firstvisual marker having a first color, a second visual marker having asecond color, a third visual marker having a third color, and a fourthvisual marker having a fourth color.

Embodiment 23

The system according to any one of embodiments 17-22, wherein a firstgroup of the plurality of groups of visual markers includes a firstvisual maker having a first color, a second visual marker having thefirst color, a third visual marker having the first color, and a fourthvisual marker having the first color.

Embodiment 24

The system according to any one of embodiments 17-23, further comprisinga mobile device including a housing, wherein the camera, the one or moreprocessors, the memory device, or any combination thereof, are at leastpartially disposed within the housing of the mobile device.

Embodiment 25

A motion tracking element configured to be coupled to an oral hygienedevice, the motion tracking element comprising a body, a pattern on anouter surface of the body, a plurality of groups of visual markers onthe outer surface of the body.

Embodiment 26

The motion tracking element according to embodiment 25, wherein the bodyincludes a first portion and a second portion.

Embodiment 27

The motion tracking element according to any one of embodiments 25 and26, wherein the first portion of the body is configured to be coupled tothe oral hygiene device.

Embodiment 28

The motion tracking element according to any one of embodiments 25-27,wherein the second portion of the body has a generally spherical shape.

Embodiment 29

The motion tracking element according to any one of embodiments 25-28,wherein the plurality of groups of visual markers protrude from theouter surface of the body.

Embodiment 30

The motion tracking element according to any one of embodiments 25-29,wherein the pattern is printed on the outer surface of the body.

Embodiment 31

The motion tracking element according to any one of embodiments 25-30,wherein the printed pattern includes a plurality of indicators and abackground.

Embodiment 32

The motion tracking element according to any one of embodiments 25-31,wherein the background has a first color and the plurality of indicatorshas a second color that is different than the first color.

Embodiment 33

The motion tracking element according to any one of embodiments 25-32,wherein the plurality of groups of visual markers includes at least afirst group of visual markers, a second group of visual markers, a thirdgroup of visual markers, and a fourth group of visual markers, one ormore visual markers of the first group of visual markers having a firstcolor, one or more visual markers of the second group of visual markershaving a second color, one or more visual markers of the third group ofvisual markers having a third color, and one or more visual markers ofthe fourth group of visual markers having a fourth color.

Embodiment 34

The motion tracking element according to any one of embodiments 25-33,wherein the first color, the second color, the third color, and thefourth color are different and distinct from one another.

Embodiment 35

The motion tracking element according to any one of embodiments 25-34,wherein each of the first color, the second color, the third color, andthe fourth color is blue, green, purple, yellow, red, orange, or anycombination thereof.

What is claimed is:
 1. A method for estimating a pose of an oral hygienedevice relative to a location, the oral hygiene device including apattern and a plurality of groups of visual markers, the methodcomprising: receiving image data reproducible as an image of at least aportion of the oral hygiene device; analyzing, using one or moreprocessors, the image data to identify a region of interest within theimage, the region of interest including at least a portion of thepattern therein; identifying, using at least one of the one or moreprocessors, all candidate visual markers from the plurality of groups ofvisual markers within the region of interest; obtaining a first proposedthree-dimensional pose of the oral hygiene device; validating the firstproposed three-dimensional pose of the oral hygiene device, whereinvalidating the first proposed three dimensional pose includes: based onthe proposed three-dimensional pose of the oral hygiene device,predicting a position within the region of interest for a predeterminednumber of the candidate visual markers; comparing the predictedpositions for the predetermined number of the candidate visual markerswith actual positions of all of the candidate visual markers within theregion of interest; and determining that at least a substantial portionof the predicted positions correspond with the actual positions; andobtaining a second proposed three-dimensional pose of the oral hygienedevice based on the validated first proposed three-dimensional pose. 2.The method of claim 1, wherein responsive to identifying the region ofinterest, segmenting, using at least one of the one or more processors,the region of interest into a plurality of sub-regions, each of theplurality of sub-regions being defined by a plurality of pixels having acommon color.
 3. The method of claim 1, wherein the obtaining the firstproposed three-dimensional pose of the oral hygiene device includes:creating a plurality of distinct sets of the candidate visual markers;selecting a first one of the plurality of distinct sets of the candidatevisual markers; selecting a first one of a plurality of distinct sets ofmodel markers associated with a three-dimensional model of the oralhygiene device; and evaluating a set of the candidate visual markers anda set of model markers using a perspective-three-point algorithm toobtain the proposed three-dimensional pose of the oral hygiene device.4. The method of claim 1, wherein the identifying all candidate visualmarkers is based on a shape and a color of each of the plurality ofsub-regions.
 5. The method of claim 1, wherein each of the plurality ofdistinct sets of the candidate visual markers includes at least fourcandidate visual markers and each of the plurality of distinct sets ofthe model markers includes at least four model markers.
 6. The method ofclaim 1, further comprising: receiving a second set of image datareproducible as a second image of at least a portion of the oral hygienedevice; identifying a second region of interest within the second imagebased on the validated three-dimensional pose of the oral hygienedevice.
 7. The method of claim 1, further comprising: adjusting, basedon the validated three-dimensional pose of the oral hygiene device, athreshold for segmenting the second region of interest to aid inidentifying pixels having different colors in the second region ofinterest.
 8. A method for estimating a pose of an oral hygiene devicerelative to a location, the oral hygiene device including a pattern anda plurality of groups of visual markers, the method comprising:receiving image data reproducible as an image of at least a portion ofthe oral hygiene device; analyzing, using one or more processors, theimage data to identify a region of interest within the image, the regionof interest including at least a portion of the pattern therein, whereinthe analyzing the image data includes using one or more filters, the oneor more filters including a movement filter, a color filter, a shapefilter, or any combination thereof; identifying, using at least one ofthe one or more processors, all candidate visual markers from theplurality of groups of visual markers within the region of interest;obtaining a first proposed three-dimensional pose of the oral hygienedevice; validating the first proposed three-dimensional pose of the oralhygiene device; and obtaining a second proposed three-dimensional poseof the oral hygiene device based on the validated first proposedthree-dimensional pose.
 9. A method for estimating a pose of an oralhygiene device relative to a location, the oral hygiene device includinga pattern and a plurality of groups of visual markers, the methodcomprising: (a) receiving image data reproducible as an image of atleast a portion of the oral hygiene device; (b) analyzing, using one ormore processors, the image data to identify a region of interest withinthe image, the region of interest including at least a portion of thepattern therein; (c) responsive to identifying the region of interest,segmenting, using at least one of the one or more processors, the regionof interest into a plurality of sub-regions, each of the plurality ofsub-regions being defined by a plurality of pixels having a commoncolor; (d) identifying, using at least one of the one or moreprocessors, all candidate visual markers from the plurality of groups ofvisual markers within the region of interest; (e) creating a pluralityof distinct sets of the candidate visual markers; (f) selecting a firstone of the plurality of distinct sets of the candidate visual markers;(g) selecting a first one of a plurality of distinct sets of modelmarkers associated with a three-dimensional model of the oral hygienedevice; (h) evaluating the selected set of the candidate visual markersand the selected set of model markers using a perspective-three-pointalgorithm to obtain a proposed three-dimensional pose of the oralhygiene device; (i) based on the proposed three-dimensional pose of theoral hygiene device, predicting a position within the region of interestfor a predetermined number of the candidate visual markers; (j)comparing the predicted positions for the predetermined number of thecandidate visual markers with actual positions of all of the candidatevisual markers within the region of interest; (k) responsive to adetermination that at least a substantial portion of the predictedpositions correspond with the actual positions, validating the proposedthree-dimensional pose; and (l) responsive to a determination that lessthan the substantial portion of the predicted positions correspond withthe actual positions, repeating steps (f)-(k).
 10. The method of claim9, further including responsive to the proposed three-dimensional posebeing validated, comparing all of the candidate visual markers and allof the model markers using an algorithm to obtain a second proposedthree-dimensional pose of the oral hygiene device.
 11. The method ofclaim 9, wherein the analyzing the first image data includes using oneor more filters, the one or more filters including a movement filter, acolor filter, a shape filter, or any combination thereof.
 12. The methodof claim 9, wherein the identifying all candidate visual markers isbased on a shape and a color of each of the plurality of sub-regions.13. The method of claim 9, wherein each of the plurality of distinctsets of the candidate visual markers includes at least four candidatevisual markers and each of the plurality of distinct sets of the modelmarkers includes at least four model markers.
 14. The method of claim 9,further comprising: receiving a second set of image data reproducible asa second image of at least a portion of the oral hygiene device;identifying a second region of interest within the second image based onthe validated three-dimensional pose of the oral hygiene device.
 15. Themethod of claim 14, further comprising: adjusting, based on thevalidated three-dimensional pose of the oral hygiene device, a thresholdfor segmenting the second region of interest to aid in identifyingpixels having different colors in the second region of interest.
 16. Amotion tracking system comprising: an oral hygiene device including ahead and a handle; a tracking element coupled to the oral hygiene deviceincluding a pattern and a plurality of groups of visual markers; acamera; one or more processors; and a memory device storing instructionsthat, when executed by at least one of the one or more processors causethe motion tracking system to, capture, using the camera, an image of atleast a portion of the oral hygiene device; analyze, using at least oneof the one or more processors, the image to identify a region ofinterest within the image, the region of interest including at least aportion of the pattern of the tracking element therein; identify, usingat least one of the one or more processors, all candidate visual markersfrom the plurality of groups of visual markers within the region ofinterest; create a plurality of distinct sets of the candidate visualmarkers; select a first one of the plurality of distinct sets of thecandidate visual markers; select a first one of a plurality of distinctsets of model markers associated with a three-dimensional model of theoral hygiene device stored in the memory device; evaluate the selectedset of the candidate visual markers and the selected set of modelmarkers using a perspective-three-point algorithm to obtain a proposedthree-dimensional pose of the oral hygiene device; based on the proposedthree-dimensional pose of the oral hygiene device, predict a positionwithin the region of interest for a predetermined number of thecandidate visual markers; compare the predicted positions for thepredetermined number of the candidate visual markers with actualpositions of all of the candidate visual markers within the region ofinterest; and responsive to a determination that at least a substantialportion of the predicted positions correspond with the actual positions,validate the proposed three-dimensional pose.